A deep learning radiomics model for predicting non-sentinel lymph node metastases in early-stage breast cancer patients.
Authors
Affiliations (7)
Affiliations (7)
- Department of Medical Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
- School of AI and Advanced Computing, XJTLU Entrepreneur College (Taicang), Xi'an Jiaotong-Liverpool University, Suzhou, China.
- Department of Computer Science, University of Liverpool, Liverpool, UK.
- Department of Radiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China.
- School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou, China.
- Department of Mathematical Sciences, University of Liverpool, Liverpool, UK.
Abstract
To develop and validate a deep learning radiomics model to predict non-sentinel lymph node (NSLN) metastases in early-stage breast cancer patients with 1-2 positive sentinel lymph node (SLN) metastases. This retrospective and prospective study encompassed 1,647 patients. Clinical, pathological information, and axillary ultrasound (AUS) findings, collected. Radiomic features of breast cancer lesions were extracted from the ultrasound images. We developed predictive models based on clinical factors alone (C model), clinical factors coupled with AUS (CA model), and clinical factors integrated with both AUS and radiomic features (CAR model). The predictive performance of each model was evaluated via the area under the curve (AUC), decision curve analysis (DCA), and calibration curve analysis. The AUC values for the C model, CA model and CAR model in the test cohort were 0.812, 0.850, and 0.994, respectively. Notably, the CAR model exhibited significantly superior predictive capability compared to both the C model and CA model. In subgroups analyses, the CAR model also achieved the optimal predictive performance. The DCA curve confirmed that the CAR model possessed significant clinical implications. The CAR model had the capability to predict NSLN metastases in early-stage breast cancer with 1-2 positive SLN metastases.